Using Neural Networks to Build Robust Hourly Models

Our first brown bag seminar of the year is entitled, “Using Neural Networks to Build Robust Hourly Models.” Neural networks are flexible functional forms that learn about nonlinear relationships from the data. These models can be used to identify nonlinearities and variable interactions and to construct x variables that embody these relationships. Learn more about these variables and how they can be used in regression models that have rich relationships that are also simple and robust.

Participation is free, but prior registration is required. Each seminar lasts approximately one hour, allowing 45 minutes for the presentation and 15 minutes for questions. Seminars start at noon PST. If you cannot attend a seminar or missed one, don’t worry. Your registration ensures that a link to the recording will be sent to you automatically approximately one week after the seminar date.

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Paige Schaefer directs various web-based projects, including brown bag seminars, internet surveys, and other web-based projects and services. Schaefer manages Itron’s Energy Forecasting Group (EFG), which supports end-use data development, the Statistical End-use Approach (SAE) and coordinates their annual meeting for discussing end-use modeling and forecasting issues. In addition, Schaefer develops, manages and executes marketing campaigns for forecasting products and services and provides software support and documentation. She is responsible for project accounting and support, financial budgeting, accounting and invoicing. Schaefer received a B.S. in Business Administration from San Diego State University with an emphasis in Marketing.

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